Vol. 2 Issue 3
Year:2014
Issue:May-Jul
Title:Tracking Path Control Of Robotic Manipulators Using Radial Basis Function Neural Network
Author Name:Sheilza Jain and Anika Chhabra
Synopsis:
Robotic manipulators have been extensively used in the industrial applications such as paint spraying, welding, accurate positioning system etc. where joint angles of robotic manipulators are directed to follow some given trajectories as close as possible. Therefore, trajectory tracking problem of robotic manipulators is the most significant and fundamental task for researchers to work upon. Robotic manipulator systems are inevitably subject to structured and unstructured uncertainties resulting in imprecision of its dynamical models and it is difficult to obtain a suitable mathematical model for the robotic control scheme. Robotic manipulators are dynamically coupled, multi-inputmulti- output, non-linear and time variant complex systems. This paper presents the dynamics of two link robotic manipulator. In this paper, PID (Proportional Integral Derivative), CTC (Computed Torque Control), SMC (Sliding Mode Control) and RBFNN (Radial Basis Function Neural Network) controllers are designed and implemented to the joint position control of two link robotic manipulators for pre-defined trajectory tracking control. Simulated results for different controllers are compared to show reduction in tracking error and performance improvement of two link robotic manipulators. Tracking performance and error comparison graphs are presented to demonstrates the performance of the proposed controllers. Further, comparison between chattering of SMC and RBFNN-SMC for joint 1 and joint 2 is also shown. The simulation work is carried out in MATLAB environment.
Year:2014
Issue:May-Jul
Title:Tracking Path Control Of Robotic Manipulators Using Radial Basis Function Neural Network
Author Name:Sheilza Jain and Anika Chhabra
Synopsis:
Robotic manipulators have been extensively used in the industrial applications such as paint spraying, welding, accurate positioning system etc. where joint angles of robotic manipulators are directed to follow some given trajectories as close as possible. Therefore, trajectory tracking problem of robotic manipulators is the most significant and fundamental task for researchers to work upon. Robotic manipulator systems are inevitably subject to structured and unstructured uncertainties resulting in imprecision of its dynamical models and it is difficult to obtain a suitable mathematical model for the robotic control scheme. Robotic manipulators are dynamically coupled, multi-inputmulti- output, non-linear and time variant complex systems. This paper presents the dynamics of two link robotic manipulator. In this paper, PID (Proportional Integral Derivative), CTC (Computed Torque Control), SMC (Sliding Mode Control) and RBFNN (Radial Basis Function Neural Network) controllers are designed and implemented to the joint position control of two link robotic manipulators for pre-defined trajectory tracking control. Simulated results for different controllers are compared to show reduction in tracking error and performance improvement of two link robotic manipulators. Tracking performance and error comparison graphs are presented to demonstrates the performance of the proposed controllers. Further, comparison between chattering of SMC and RBFNN-SMC for joint 1 and joint 2 is also shown. The simulation work is carried out in MATLAB environment.
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